✦ Luna Orbit — AI & Machine Learning

Staff Data Scientist, AI - Hybrid

at NRG Energy

📍 UT, US, 84043 Hybrid Posted March 13, 2026
Type Not Specified
Experience mid
Exp. Years 5+ years
Education Not specified
Category AI & Machine Learning

NRG Energy seeks a staff data scientist to develop predictive models for energy forecasting, demand response, and optimization in smart home environments, leveraging AI and large-scale sensor data.

  • Develop Predictive Models
  • Optimize Energy Operations
  • Transform Legacy Data
  • Collaborate with Engineering
  • Communicate Insights

The role involves building and deploying advanced ML models using Python, PySpark, Databricks, and GCP, focusing on energy forecasting, anomaly detection, and demand response optimization.

The ideal candidate is a mid-level data scientist with 5+ years of experience in predictive modeling, working with large-scale sensor and event data in energy or IoT environments. They are proficient in Python and distributed computing platforms like Databricks and GCP, capable of deploying scalable ML models.

Predictive ModelingExperience with large-scale event and sensor dataProficiency in PythonExperience with distributed compute environmentsModel deployment experienceStatistical analysisFeature engineering
Energy forecastingThermal modelingDemand Response optimizationEnergy marketsDistributed Energy ResourcesVPPLLMGenerative AI
PythonPandasNumPyscikit-learnPySparkSparkDatabricksGCP
Predictive ModelingForecastingMLRegressionGradient BoostingTime-SeriesCausal InferencePythonPandasNumPyscikit-learnPySparkSparkDatabricksGCP
Predictive ModelingForecastingMLRegressionGradient BoostingTime-SeriesCausal InferencePythonPandasNumPyscikit-learnPySparkSparkDatabricksGCP
CommunicationStorytellingCollaborationProblem-solvingAnalytical Thinking

Preferred

MS in StatisticsPhD in EngineeringData Science Certification
Industry Energy, IoT, Smart Home, Data & Analytics
Job Function Design and deploy predictive analytics and ML models to improve energy efficiency and demand response in smart home systems.
Predictive ModelsForecastingMLRegressionGradient BoostingTime-SeriesCausal InferencePythonPySparkDatabricksGCPSensor DataEnergy ForecastingDemand ResponseVPPAIGenerative AIPredictive ModelingEnergy

Lack of experience with energy forecasting or demand response, No proficiency in Python or distributed compute environments, Unwilling to work in hybrid mode in Utah, No experience with sensor or IoT data

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